SoroushVahidi/scidocs huggingface dataset:
Research Paper: Automatic Detection of Acute Bacterial Pneumonia from Chest X-ray Reports
(2000)

OBJECTIVE
To evaluate the performance of a natural language processing system in extracting pneumonia-related concepts from chest x-ray reports.


METHODS



DESIGN
Four physicians, three lay persons, a natural language processing system, and two keyword searches (designated AAKS and KS) detected the presence or absence of three pneumonia-related concepts and inferred the presence or absence of acute bacterial pneumonia from 292 chest x-ray reports. Gold standard: Majority vote of three independent physicians. Reliability of the gold standard was measured.


OUTCOME MEASURES
Recall, precision, specificity, and agreement (using Finn's R: statistic) with respect to the gold standard. Differences between the physicians and the other subjects were tested using the McNemar test for each pneumonia concept and for the disease inference of acute bacterial pneumonia.


RESULTS
Reliability of the reference standard ranged from 0.86 to 0.96. Recall, precision, specificity, and agreement (Finn R:) for the inference on acute bacterial pneumonia were, respectively, 0.94, 0.87, 0.91, and 0.84 for physicians; 0.95, 0.78, 0.85, and 0.75 for natural language processing system; 0.46, 0.89, 0.95, and 0.54 for lay persons; 0.79, 0.63, 0.71, and 0.49 for AAKS; and 0.87, 0.70, 0.77, and 0.62 for KS. The McNemar pairwise comparisons showed differences between one physician and the natural language processing system for the infiltrate concept and between another physician and the natural language processing system for the inference on acute bacterial pneumonia. The comparisons also showed that most physicians were significantly different from the other subjects in all pneumonia concepts and the disease inference.


CONCLUSION
In extracting pneumonia related concepts from chest x-ray reports, the performance of the natural language processing system was similar to that of physicians and better than that of lay persons and keyword searches. The encoded pneumonia information has the potential to support several pneumonia-related applications used in our institution. The applications include a decision support system called the antibiotic assistant, a computerized clinical protocol for pneumonia, and a quality assurance application in the radiology department.
Valuation of IT Investments Using Real Options Theory
(2013)

Real Options Theory is often applied to the valuation of IT investments. The application of Real Options Theory is generally accompanied by a monetary valuation of real options through option pricing models which in turn are based on restrictive assumptions and thus subject to criticism. Therefore, this paper analyzes the application of option pricing models for the valuation of IT investments. A structured literature review reveals the types of IT investments which are valuated with Real Options Theory in scientific literature. These types of IT investments are further investigated and their main characteristics are compared to the restrictive assumptions of traditional option pricing models. This analysis serves as a basis for further discussion on how the identified papers address these assumptions. The results show that a lot of papers do not account for critical assumptions, although it is known that the assumptions are not fulfilled. Moreover, the type of IT investment determines the criticality of the assumptions. Additionally, several extensions or adaptions of traditional option pricing models can be found which provide the possibility of relaxing critical assumptions. Researchers can profit from the results derived in this paper in two ways: First, which assumptions can be critical for various types of IT investments are demonstrated. Second, extensions of option pricing models that relax critical assumptions are introduced.
The source code control system
(1975)

The Source Code Control System (SCCS) is a software tool designed to help programming projects control changes to source code. It provides facilities for storing, updating, and retrieving all versions of modules, for controlling updating privileges for identifying load modules by version number, and for recording who made each software change, when and where it was made, and why. This paper discusses the SCCS approach to source code control, shows how it is used and explains how it is implemented.
Scheduling Real-Time Transactions: A Performance Evaluation
(1988)

Managing transactions with real-time requirements presents many new problems. In this paper we address several: How can we schedule transactions with deadlines? How do the real-time constraints affect concurrency control? How should overloads be handled? How does the scheduling of 1/0 requests affect the timeliness of transactions? How should exclusive and shared locking be handled? We describe a new group of algorithms for scheduling real-time transactions that produce serializable schedules. We present a model for scheduling transactions with deadlines on a single processor disk resident database system, and evaluate the scheduling algorithms through detailed simulation experiments.
Magnetic field effects on plant growth, development, and evolution
(2014)

The geomagnetic field (GMF) is a natural component of our environment. Plants, which are known to sense different wavelengths of light, respond to gravity, react to touch and electrical signaling, cannot escape the effect of GMF. While phototropism, gravitropism, and tigmotropism have been thoroughly studied, the impact of GMF on plant growth and development is not well-understood. This review describes the effects of altering magnetic field (MF) conditions on plants by considering plant responses to MF values either lower or higher than those of the GMF. The possible role of GMF on plant evolution and the nature of the magnetoreceptor is also discussed.
Attentive Tensor Product Learning for Language Generation and Grammar Parsing
(2018)

This paper proposes a new architecture — Attentive Tensor Product Learning (ATPL) — to represent grammatical structures in deep learning models. ATPL is a new architecture to bridge this gap by exploiting Tensor Product Representations (TPR), a structured neural-symbolic model developed in cognitive science, aiming to integrate deep learning with explicit language structures and rules. The key ideas of ATPL are: 1) unsupervised learning of role-unbinding vectors of words via TPR-based deep neural network; 2) employing attention modules to compute TPR; and 3) integration of TPR with typical deep learning architectures including Long Short-Term Memory (LSTM) and Feedforward Neural Network (FFNN). The novelty of our approach lies in its ability to extract the grammatical structure of a sentence by using role-unbinding vectors, which are obtained in an unsupervised manner. This ATPL approach is applied to 1) image captioning, 2) part of speech (POS) tagging, and 3) constituency parsing of a sentence. Experimental results demonstrate the effectiveness of the proposed approach.
Interrater reliability of a modified Ashworth scale of muscle spasticity.
(1987)

We undertook this investigation to determine the interrater reliability of manual tests of elbow flexor muscle spasticity graded on a modified Ashworth scale. We each independently graded the elbow flexor muscle spasticity of 30 patients with intracranial lesions. We agreed on 86.7% of our ratings. The Kendall's tau correlation between our grades was .847 (p less than .001). Thus, the relationship between the raters' judgments was significant and the reliability was good. Although the results were limited to the elbow flexor muscle group, we believe them to be positive enough to encourage further trials of the modified Ashworth scale for grading spasticity.
Improved Plagiarism Detection Algorithm Based on Abstract Syntax Tree
(2013)

Statements with conditionals are widely used in C, C++ and java, such as if and while statements and they are easy to plagiarize by adjusting the logical structure of the corresponding statements. However, the existing relative algorithms and tools cannot effectively detect code plagiarism of these statements. This paper puts forward an improved code plagiarism detection algorithm based on abstract syntax tree. The algorithm calculates the hash value for each node of the abstract syntax tree, and compares the hash values node by node. Based on this, it analyzes the if-statement plagiarism, as if-statements are representative in the statements with conditionals, and puts forward the corresponding detection schemes in order to detect plagiarism effectively. After that, with the results of many experiments, the algorithm is proved effective on detecting if-statement plagiarisms.
Penile Implants among Prisoners—A Cause for Concern?
(2013)

BACKGROUND
We report the prevalence of penile implants among prisoners and determine the independent predictors for having penile implants. Questions on penile implants were included in the Sexual Health and Attitudes of Australian Prisoners (SHAAP) survey following concerns raised by prison health staff that increasing numbers of prisoners reported having penile implants while in prison.


METHODS
Computer-Assisted Telephone Interviewing (CATI) of a random sample of prisoners was carried out in 41 prisons in New South Wales and Queensland (Australia). Men were asked, "Have you ever inserted or implanted an object under the skin of your penis?" If they responded Yes: "Have you ever done so while you were in prison?" Univariate logistic regression and logistic regression were used to determine the factors associated with penile implants.


RESULTS
A total of 2,018 male prisoners were surveyed, aged between 18 and 65 years, and 118 (5.8%) reported that they had inserted or implanted an object under the skin of their penis. Of these men, 87 (73%) had this done while they were in prison. In the multivariate analysis, a younger age, birth in an Asian country, and prior incarceration were all significantly associated with penile implants (p<0.001). Men with penile implants were also more likely to report being paid for sex (p<0.001), to have had body piercings (p<0.001) or tattoos in prison (p<0.001), and to have taken non-prescription drugs while in prison (p<0.05).


CONCLUSIONS
Penile implants appear to be fairly common among prisoners and are associated with risky sexual and drug use practices. As most of these penile implants are inserted in prison, these men are at risk of blood borne viruses and wound infection. Harm reduction and infection control strategies need to be developed to address this potential risk.
Air-filled substrate integrated waveguide — A flexible and low loss technological platform
(2017)

In this paper, the air-filled substrate integrated waveguide (AFSIW), offering a technological platform for the design of high performance millimeterwave self-packaged substrate integrated components and systems, is presented. AFSIW is based on low-cost printed circuit board (PCB). Several components, including antennas, filters and couplers, have been theoretically studied and experimentally demonstrated up to 60 GHz. This technology, surpassing its dielectric-filled SIW (DFSIW) counterpart, is expected by the authors to replace the rectangular waveguide technology for future low-cost extremely high data rate communication systems and highly sensitive sensors operating at millimeterwave and beyond.
Attention Deficit Hyperactivity Disorder: Is There an App for That? Suitability Assessment of Apps for Children and Young People With ADHD
(2017)

BACKGROUND
Attention-deficit/hyperactivity disorder (ADHD) is a complex highly comorbid disorder, which can have a huge impact on those with ADHD, their family, and the community around them. ADHD is currently managed using pharmacological and nonpharmacological interventions. However, with advances in technology and an increase in the use of mobile apps, managing ADHD can be augmented using apps specifically designed for this population. However, little is known regarding the suitability and usability of currently available apps.


OBJECTIVE
The aim of this study was to explore the suitability of the top 10 listed apps for children and young people with ADHD and clinicians who work with them. It is hypothesized that mobile apps designed for this population could be more suitably designed for this population.


METHODS
The top 10 listed apps that are specifically targeted toward children and young people with ADHD in the United Kingdom were identified via the Google Play (n=5) and iTunes store (n=5). Interviews were then undertaken with 5 clinicians who specialize in treating this population and 5 children and young people with ADHD themselves, to explore their opinions of the 10 apps identified and what they believe the key components are for apps to be suitable for this population.


RESULTS
Five themes emerged from clinician and young people interviews: the accessibility of the technology, the importance of relating to apps, addressing ADHD symptoms and related difficulties, age appropriateness, and app interaction. Three additional themes emerged from the clinician interviews alone: monitoring symptoms, side effects and app effect on relationships, and the impact of common comorbid conditions. The characteristics of the apps did not appear to match well with the views of our sample.


CONCLUSIONS
These findings suggest that the apps may not be suitable in meeting the complex needs associated with this condition. Further research is required to explore the value of apps for children and young people with ADHD and their families and, in particular, any positive role for apps in the management of ADHD in this age group. A systematic review on how technology can be used to engage this population and how it can be used to help them would be a useful way forward. This could be the platform to begin exploring the use of apps further.
Scale Up vs. Scale Out in Cloud Storage and Graph Processing Systems
(2015)

Deployers of cloud storage and iterative processing systems typically have to deal with either dollar budget constraints or throughput requirements. This paper examines the question of whether such cloud storage and iterative processing systems are more cost-efficient when scheduled on a COTS (scale out) cluster or a single beefy (scale up) machine. We experimentally evaluate two systems: 1) a distributed key-value store (Cassandra), and 2) a distributed graph processing system (Graph Lab). Our studies reveal scenarios where each option is preferable over the other. We provide recommendations for deployers of such systems to decide between scale up vs. Scale out, as a function of their dollar or throughput constraints. Our results indicate that there is a need or adaptive scheduling in heterogeneous clusters containing scale up and scale out nodes.
The ASK Corpus - a Language Learner Corpus of Norwegian as a Second Language
(2006)

In our paper we present the design and interface of ASK, a language learner corpus of Norwegian as a second language which contains essays collected from language tests on two different proficiency levels as well as personal data from the test takers. In addition, the corpus also contains texts and relevant personal data from native Norwegians as control data. The texts as well as the personal data are marked up in XML according to the TEI Guidelines. In order to be able to classify “errors” in the texts, we have introduced new attributes to the TEI corr and sic tags. For each error tag, a correct form is also in the text annotation. Finally, we employ an automatic tagger developed for standard Norwegian, the “Oslo-Bergen Tagger”, together with a facility for manual tag correction. As corpus query system, we are using the Corpus Workbench developed at the University of Stuttgart together with a web search interface developed at Aksis, University of Bergen. The system allows for searching for combinations of words, error types, grammatical annotation and personal data.
WordFreak: An Open Tool for Linguistic Annotation
(2003)

WordFreak is a natural language annotation tool that has been designed to be easy to extend to new domains and tasks. Specifically, a plug-in architecture has been developed which allows components to be added to WordFreak for customized visualization, annotation specification, and automatic annotation, without re-compilation. The APIs for these plug-ins provide mechanisms to allow automatic annotators or taggers to guide future annotation to supports active learning. At present WordFreak can be used to annotate a number of different types of annotation in English, Chinese, and Arabic including: constituent parse structure and dependent annotations, and ACE named-entity and coreference annotation. The Java source code for WordFreak is distributed under the Mozilla Public License 1.1 via SourceForge at: http://wordfreak.sourceforge.net. This site also provides screenshots, and a web deployable version of WordFreak.
Comparison between JSON and XML in Applications Based on AJAX
(2012)

As the core technology of Web 2.0, Ajax has caught more and more attention. Xml, as the traditional data load format, needs to be resolved by DOM (Document Object Model ) both in client-side and server-side, which wastes system resource and makes a great reduction of user-friendliness. In this paper, a light-weightdata-interchanging format-JSON (Java Script Object Notation) will be introduced, which provides a higher level of flexibility and efficiency. We make a comparison between JSON and XML through expriment, then use JSON as data-transfering format in an actual project. Results show that JSON is more suitable as a data-loading tool for Ajax applications.
Characterization of double-layer capacitors (DLCs) for power electronics applications
(1998)

The double-layer capacitor (DLC) for power applications is a new device. A simple resistive capacitive equivalent circuit is insufficient to characterize its terminal behaviour. Based on physical reasoning, an equivalent circuit is proposed to provide the power electronics engineer with a model for the terminal behaviour of the DLC. The equivalent model consists of three Re branches, one of them with a voltage dependent capacitor. A method to identify the circuit parameters is presented. Measurements of carbon-based DLCs for power applications are presented, analysed, and the equivalent circuit response is compared with experimental results.
A novel spring mechanism to reduce energy consumption of robotic arms
(2012)

Most conventional robotic arms use motors to accelerate the manipulator. This leads to an unnecessary high energy consumption when performing repetitive tasks. This paper presents an approach to reduce energy consumption in robotic arms by performing its repetitive tasks with the help of a parallel spring mechanism. A special non-linear spring characteristic has been achieved by attaching a spring to two connected pulleys. This parallel spring mechanism provides for the accelerations of the manipulator without compromising its ability to vary the task parameters (the time per stroke, the displacement per stroke the grasping time and the payload). The energy consumption of the arm with the spring mechanism is compared to that of the same arm without the spring mechanism. Optimal control studies show that the robotic arm uses 22% less energy due to the spring mechanism. On the 2 DOF prototype, we achieved an energy reduction of 20%. The difference was due to model simplifications. With a spring mechanism, there is an extra energetic cost, because potential energy has to be stored into the spring during startup. This cost is equal to the total energy savings of the 2 DOF arm during 8 strokes. Next, there could have been an energetic cost to position the manipulator outside the equilibrium position. We have designed the spring mechanism in such a way that this holding cost is negligible for a range of start- and end positions. The performed experiments showed that the implementation of the proposed spring mechanism results in a reduction of the energy consumption while the arm is still able to handle varying task parameters.
A Method for Compact Image Representation Using Sparse Matrix and Tensor Projections Onto Exemplar Orthonormal Bases
(2010)

We present a new method for compact representation of large image datasets. Our method is based on treating small patches from a 2-D image as matrices as opposed to the conventional vectorial representation, and encoding these patches as sparse projections onto a set of exemplar orthonormal bases, which are learned a priori from a training set. The end result is a low-error, highly compact image/patch representation that has significant theoretical merits and compares favorably with existing techniques (including JPEG) on experiments involving the compression of ORL and Yale face databases, as well as a database of miscellaneous natural images. In the context of learning multiple orthonormal bases, we show the easy tunability of our method to efficiently represent patches of different complexities. Furthermore, we show that our method is extensible in a theoretically sound manner to higher-order matrices (¿tensors¿). We demonstrate applications of this theory to compression of well-known color image datasets such as the GaTech and CMU-PIE face databases and show performance competitive with JPEG. Lastly, we also analyze the effect of image noise on the performance of our compression schemes.
Place-Its: A Study of Location-Based Reminders on Mobile Phones
(2005)

Context-awareness can improve the usefulness of automated reminders. However, context-aware reminder applications have yet to be evaluated throughout a person’s daily life. Mobile phones provide a potentially convenient and truly ubiquitous platform for the detection of personal context such as location, as well as the delivery of reminders. We designed Place-Its, a location-based reminder application that runs on mobile phones, to study people using location-aware reminders throughout their daily lives. We describe the design of Place-Its and a two-week exploratory user study. The study reveals that location-based reminders are useful, in large part because people use location in
MULTISCALE ENTANGLEMENT RENORMALIZATION ANSATZ
(2017)

The goal of this paper is to demonstrate a method for tensorizing neural networks based upon an efficient way of approximating scale invariant quantum states, the Multi-scale Entanglement Renormalization Ansatz (MERA). We employ MERA as a replacement for linear layers in a neural network and test this implementation on the CIFAR-10 dataset. The proposed method outperforms factorization using tensor trains, providing greater compression for the same level of accuracy and greater accuracy for the same level of compression. We demonstrate MERAlayers with 3900 times fewer parameters and a reduction in accuracy of less than 1% compared to the equivalent fully connected layers.